From 17cdd165cbfb144ebe20374af3f6e38bb2bc7f0c Mon Sep 17 00:00:00 2001 From: Hasnaat Hussain Date: Thu, 13 Aug 2026 01:17:50 +0500 Subject: [PATCH] test(utils): cover embedding dimensions in core-utils shard Signed-off-by: Hasnaat Hussain --- .../test_embedding_optional_params.py | 51 +++++++++++++++++++ tests/test_litellm/test_utils.py | 48 ----------------- 2 files changed, 51 insertions(+), 48 deletions(-) create mode 100644 tests/test_litellm/litellm_core_utils/test_embedding_optional_params.py diff --git a/tests/test_litellm/litellm_core_utils/test_embedding_optional_params.py b/tests/test_litellm/litellm_core_utils/test_embedding_optional_params.py new file mode 100644 index 00000000000..6a044a5680a --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/test_embedding_optional_params.py @@ -0,0 +1,51 @@ +import pytest + +import litellm + + +@pytest.mark.parametrize("provider", ["azure", "together_ai"]) +def test_embedding_dimensions_drop_params_for_openai_compatible_provider(provider): + previous_drop_params = litellm.drop_params + try: + litellm.drop_params = False + dropped = litellm.utils.get_optional_params_embeddings( + model=f"{provider}/dummy-model", + custom_llm_provider=provider, + dimensions=512, + drop_params=True, + ) + assert "dimensions" not in dropped + + litellm.drop_params = True + dropped_globally = litellm.utils.get_optional_params_embeddings( + model=f"{provider}/dummy-model", + custom_llm_provider=provider, + dimensions=512, + ) + assert "dimensions" not in dropped_globally + + litellm.drop_params = False + preserved = litellm.utils.get_optional_params_embeddings( + model=f"{provider}/dummy-model", + custom_llm_provider=provider, + dimensions=512, + ) + assert preserved["dimensions"] == 512 + + litellm.drop_params = True + model_supported = litellm.utils.get_optional_params_embeddings( + model=f"{provider}/text-embedding-3-small", + custom_llm_provider=provider, + dimensions=512, + ) + assert model_supported["dimensions"] == 512 + + explicitly_allowed = litellm.utils.get_optional_params_embeddings( + model=f"{provider}/legacy-model", + custom_llm_provider=provider, + dimensions=512, + allowed_openai_params=["dimensions"], + ) + assert explicitly_allowed["dimensions"] == 512 + finally: + litellm.drop_params = previous_drop_params diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 438c0e39908..6524353aa48 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -733,54 +733,6 @@ def test_cohere_embedding_optional_params(): assert optional_params is not None -@pytest.mark.parametrize("provider", ["azure", "together_ai"]) -def test_embedding_dimensions_drop_params_for_openai_compatible_provider(provider): - previous_drop_params = litellm.drop_params - try: - litellm.drop_params = False - dropped = litellm.utils.get_optional_params_embeddings( - model=f"{provider}/dummy-model", - custom_llm_provider=provider, - dimensions=512, - drop_params=True, - ) - assert "dimensions" not in dropped - - litellm.drop_params = True - dropped_globally = litellm.utils.get_optional_params_embeddings( - model=f"{provider}/dummy-model", - custom_llm_provider=provider, - dimensions=512, - ) - assert "dimensions" not in dropped_globally - - litellm.drop_params = False - preserved = litellm.utils.get_optional_params_embeddings( - model=f"{provider}/dummy-model", - custom_llm_provider=provider, - dimensions=512, - ) - assert preserved["dimensions"] == 512 - - litellm.drop_params = True - model_supported = litellm.utils.get_optional_params_embeddings( - model=f"{provider}/text-embedding-3-small", - custom_llm_provider=provider, - dimensions=512, - ) - assert model_supported["dimensions"] == 512 - - explicitly_allowed = litellm.utils.get_optional_params_embeddings( - model=f"{provider}/legacy-model", - custom_llm_provider=provider, - dimensions=512, - allowed_openai_params=["dimensions"], - ) - assert explicitly_allowed["dimensions"] == 512 - finally: - litellm.drop_params = previous_drop_params - - def validate_model_cost_values(model_data, exceptions=None): """ Validates that cost values in model data do not exceed 1.